IMPACT OF AI ROBOT IMAGE RECOGNITION TECHNOLOGY ON IMPROVING STUDENTS’ CONCEPTUAL UNDERSTANDING OF CELL DIVISION AND SCIENCE LEARNING MOTIVATION

This quasi-experimental study evaluates an AI robot image recognition system where 7th-grade students teach the AI to recognize cell division images, comparing learning outcomes and motivation against traditional textbook instruction. The research directly measures the impact of this AI-based 'Learning by Teaching' approach on students' conceptual understanding of cell division and science learning motivation.

This study explored the integration of neural networks and artificial intelligence in image recognition for object identification. The aim was to enhance students’ learning experiences through a "Learning by Teaching" approach, in which students act as instructors to train AI robots in recognizing objects. This research specifically focused on the cell division unit in the first grade of lower-secondary school. This study employed a quasi-experimental research design involving four seventh-grade

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